A structural Markov property for decomposable graph laws that allows control of clique intersections

DOI10.1093/biomet/asx072OpenAlexW2765670248MaRDI QIDQ5384561

Alun Thomas, Peter J. Green

Publication date: 24 June 2019

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.00554

zbMATH Keywords

Markov random fieldrandom graphmodel determinationconditional independencegraphical modelhub model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Graphical posterior predictive classification: Bayesian model averaging with particle Gibbs ⋮ Bayesian learning of weakly structural Markov graph laws using sequential Monte Carlo methods

This page was built for publication: A structural Markov property for decomposable graph laws that allows control of clique intersections